naturalistic-data

Sharing resources pertaining to naturalistic data analysis

[Emily Finn @esfinn]

If you've ever wanted guidance on how to choose a "naturalistic" stimulus for a psych study (neuroimaging and/or behavior), this one's for you! @claregrall drops some wisdom from media studies that is both theoretically interesting and practically useful ⬇️

[bioRxiv Neuroscience @biorxiv_neursci]

Movie-watching outperforms rest for functional connectivity-based prediction of behavior https://t.co/dm1Vz1WLXo #biorxiv_neursci

[Kate Humphreys (she/her) @K_L_Humphreys]

I am SO EXCITED to announce a new research tool we've been developing. This "TotTag" device (part of the SociTrack system) allows researchers to study proximity with high accuracy (including between children and caregivers). https://t.co/EFm1TmRkBC @salovphd /1

[naturalistic-data @natural_data]

We're also hosting a second session on Thurs at 8pm US Eastern / Fri 2am Paris / Fri 8am Beijing if you can't make it today!

[Emily Finn @esfinn]

Join us in a little over an hour (2pm US Eastern time) to chat about analysis methods for naturalistic data! Message me for Zoom link #OHBM2020 https://t.co/nyUAwfUePd @lukejchang @jeremyRmanning @elneurozorro @ChrisBaldassano @JuhaLahnakoski

[Emily Finn @esfinn]

Our #OHBM2020 ed course, Analysis Methods for Naturalistic Data, is live at https://t.co/jn9Gx7LsO5! We cover some of the most exciting tools for analyzing brain responses to movies and stories. Browse tutorials and videos online, or grab the code and try it on your own data!

[Context Lab @ContextMemLab]

Learn how to analyze brain responses to naturalistic stimuli from our @OHBM educational course organized by @lukejchang @esfinn @torwager @jeremyRmanning and featuring awesome tutorials and content from a growing list of 🤩 scientists! https://t.co/xmkxiJYUs8

[Emily Finn @esfinn]

We'll be hosting two Q&A and discussion sessions this week: 1) Weds 15 July at 2pm US Eastern time (via official OHBM platform), and 2) Thurs 16 July at 8pm US Eastern time (message me for Zoom link). Please join us if you can!

[The LAB Lab 🏳️‍🌈🏳️‍⚧️ @thelablab]

Our 'Naturalistic Neuroimaging Database' (NNDb v1) is ready to use. Eighty-six people did a battery of behavioural tests and watched one of 10 full-length #movies during #fMRI. That's 46,249,600,000 voxels or 6.69 days worth of data to play with. 🥳

See: https://t.co/1tMWGT6TfO

[Hayoung Song @HayoungSong5]

New preprint out! Causal understanding of narratives, and the dynamic reconfiguration of the brain using network graphs, predictive models, and hidden Markov latent state analysis
work with @BoyongPark1, Hyunjin Park, and my advisor @ShimMok
https://t.co/CzETLfV4na

[naturalistic-data @natural_data]

@yarikoptic @kanileke @esfinn @datalad Thanks @yarikoptic that would be amazing. Gin is a really nice platform, but the data transfer speeds are quite slow for large datasets.

[naturalistic-data @natural_data]

Access preprocessed Sherlock and Paranoia naturalistic neuroimaging datasets shared by @kanileke and @esfinn using @datalad https://t.co/q3GxWVkS05

[naturalistic-data @natural_data]

Watch videos providing tutorials and applications of naturalistic data analysis on our youtube channel https://t.co/PxLfGN71tc by @yaarayeshurun @parkinsoncm @ChrisBaldassano @Lindageerligs @LucyLongOwen @haxbylab @jeremyRmanning @elneurozorro @esfinn

[naturalistic-data @natural_data]

@emdupre_ @elneurozorro @talyarkoni Whoops, sorry about that. Also, link to video and tutorial https://t.co/9D3rhQp2u3.

[naturalistic-data @natural_data]

Learn how automate feature extraction of naturalistic data using Pliers toolbox by @elneurozorro and @talyarkoni https://t.co/H18qHxiIfm

[naturalistic-data @natural_data]

Learn how to visualize high dimensional naturalistic data using hypertools toolbox by @jeremyRmanning https://t.co/5JLZ2Ep8xj

[naturalistic-data @natural_data]

Learn how to model dynamic functional connectivity using Hidden Semi-Markov Models in #RStats by Heather Shappell https://t.co/72mGNO41ud

[naturalistic-data @natural_data]

Learn how to model the dynamics of naturalistic time series data using timecorr toolbox by @jeremyRmanning https://t.co/2x2LxWxnYc

[naturalistic-data @natural_data]

Learn how to decode the representation of natural language from fMRI using Python and naturalistic data by Jiwoong Park @ShimMok @HayoungSong5 https://t.co/L7wcikLBLE

[naturalistic-data @natural_data]

Learn how to apply Intersubject Correlation analysis to neuroimaging data using the Python nltools toolbox by @JuhaLahnakoski & @lukejchang https://t.co/mWeKwW4LiX

[naturalistic-data @natural_data]

Learn how to apply event segmentation and alignment in fMRI data using Hidden Markov Models and Greedy State Boundary Search using @UseBrainIAK and statesegmentation toolbox by @ChrisBaldassano & @Lindageerligs https://t.co/kYjVEBSLjO